Maria Lomeli Garcia
I am a research scientist at Babylon Health, UK. Previously, I was a research associate, working with Zoubin Ghahramani at the Machine Learning group, CBL, University of Cambridge and member of Trinity Hall college.
I studied my PhD at the Gatsby Unit, UCL, my supervisor was Yee Whye Teh. Before coming to the UK, I did an MSc in Mathematical Sciences at IIMAS,
Universidad Nacional Autónoma de México, advised by Ramsés Mena.
- Machine Learning for Healthcare
- Bayesian Nonparametrics
- Reproducing kernel Hilbert spaces
- Exact inference methods (MCMC, SMC)
- November, 2018. An arXiv preprint is available for our paper "Universal marginaliser for amortised inference and embeddings of generative models"
- September, 2018. I am reviewing for the All Bayesian Nonparametrics workshop at NIPS 2018.
- August, 2018. I am nominated to serve as the Secretary of the Bayesian Computation of ISBA, see my statement here.
- August, 2018. I am presenting a poster at the Probabilistic Programming Conference in Boston this October.
- Walecki, R., Buchard, A., Gourgoulias, K., Hart, C., Lomeli, M., Navarro, A. K. W., Zwiessele, M., Johri, S. ''Universal marginaliser for amortised inference and embeddings of generative models'' , arXiv preprint.
- Lomeli, M., Rowland, M., Gretton, A. and Ghahramani, Z., ''Antithetic and Monte Carlo kernel estimators for partial rankings'', arXiv preprint.
- Valera, I., Pradier, M., Lomeli, M. and Ghahramani, Z., ''General Latent Feature Model for Heterogeneous Datasets'', arXiv preprint.
- Lomeli, M., Favaro, S., Teh, Y. W.,'' A marginal sampler for -Stable Poisson-Kingman mixture models'', Journal of Computational and Graphical Statistics, 2017, Vol 26, 44-53 JCGS.
Favaro, S., Lomeli, M., Nipoti, B., Teh, Y.W., ''Stick-breaking representations of -stable Poisson-Kingman models'' , Electronic Journal of Statistics, 2014, Vol. 8, pp 1063-1085 EJS.
Favaro, S., Lomeli, M., Teh, Y.W.,''On a class of -stable Poisson-Kingman models and an effective marginalized sampler'', Statistics and Computing, 2014, Vol 25, pp 67-78
- Lomeli, M., Favaro, S.,Teh, Y.W., 2015, ''A hybrid sampler for Poisson-Kingman mixture models'', Neural information Processing Systems NIPS
- Sejdinovic, D., Strathmann, H., Lomeli Garcia, M., Andrieu, C., Gretton, A., 2014,''Kernel Adaptive Metropolis-Hastings'', International Conference in Machine Learning ICML
Favaro, S., Lomeli, M., Nipoti, B., Teh, Y.W., 2013, ''Stick-breaking representations of -stable Poisson-Kingman models'', Complex Data Modelling and Computationally Intensive Methods for Estimation and Prediction conference.
- Bloem-Reddy, B., Mathieu, E., Foster, A., Rainforth, T., Ge, H., Lomeli, M., Ghahramani, Z., Teh, Y.W., 2017, ''Sampling and inference for discrete random probability measures in probabilistic programs'', Approximate Inference workshop, NIPS
Theses and projects
- General Bayesian inference schemes in infinite mixture models
PhD thesis, University College London
Arxiv version: arXiv:1702.08781
(Figures 2.2 and 5.1 are not displayed properly, email me for the pdf version)
- Consistencia Posterior de Modelos Bayesianos No Paramétricos
(Posterior Consistency of Bayesian Nonparametric Models)
MSc project, UNAM
Available upon request (In Spanish)
- Qué tan "expertos" son los Expertos: Un Modelo de Evaluación y Pronóstico
Undergraduate thesis, ITAM
Available upon request (In Spanish)
- June 11, 2018. Talk at Parallelizing Monte Carlo Algorithms workshop, School of Mathematics, University of Bristol
- March 15, 2018. Talk at the CamAIML event, Microsoft research Cambridge
- February 16, 2018. Talk at the University of Glasgow, Statistics seminar
- Febryary 2, 2018. Talk at UCL, CSML Lunchtime seminar
- February 1, 2018. Talk at Amazon Cambridge research series seminar
- August 30, 2017. Talk at the 2017 SMC workshop
- June 7, 2017. Talk at the ''Congreso Bayesiano de América Latina''
- June 14, 2016. Talk at the ''Bayes Legacy'' sesssion, 13th ISBA Wold meeting in Sardinia, Italy
- June 2, 2016. Talk at the Machine Learning group, CBL, University of Cambridge
- May 5, 2016. Talk at Machine Learning reading group, CBL, University of Cambridge
- July 16, 2015. Talk at CBL, University of Cambridge
- June 22, 2015. Talk at the 10th
Bayesian Nonparametrics conference
- June 15, 2015. Talk at the 9th
Bayesian Inference for Stochastic Processes conference
- January 26, 2014. Talk
at the Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas,
Universidad Nacional Autónoma de México
- October 24, 2014. Talk
at the Computational Statistics seminar, University of Oxford
- September 24, 2014. Talk
at CBL, University of Cambridge
- March 3, 2014. Talk at the workshop
Advances in Scalable Bayesian Computation, available
- Teaching assistant, Part II Statistical modelling course, Statslab, University of Cambridge (Lent, 2018)
- Coding lab demonstrator, APTS, Statistical computing module for Statistics PhD students, University of Cambridge (December, 2017)
- Coding lab demonstrator, MLSALT1 graduate course, University of Cambridge (Michaelmas, 2017)
- Coding lab demonstrator, 3F8 undergraduate course, University of Cambridge (Lent, 2017)
Teaching assistant, Statistical Data Mining and Machine Learning MSc in Applied Statistics course, University of Oxford (Hilary term 2014 and 2015)
- Coding lab demonstrator, Kernel methods module, Introduction to machine learning graduate course, University College London (2013)
- Teaching assistant, Probabilistic and Unsupervised Learning graduate course, University College London (Autumn, 2012)
- Lecturer, Stochastic Processes, undergraduate course, Instituto Tecnológico Autónomo de México (Summer, 2011)
- 2018, Journal of Machine Learning Research
- 2017, Biometrika
- 2017, Scandinavian Journal of Statistics
- 2016, Computational Statistics and Data Analysis
- 2016, Statistics and Computing
- 2016, 2017, International Conference in Machine Learning
- 2013, 2014, 2015, 2017,2018 Neural Information Processing Systems
- 2014, 2015,
I was one of the organisers of our CSML Lunch Talk Series.